17 research outputs found

    Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

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    Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention

    Framework Of Machine Learning Techniques For Cancer Prediction

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    The goal of this work is to design a machine-learning model that accurately predicts skin, lung, and skin cancer. Cancer-related clinical, demographic, and lifestyle factors were included in the dataset used to train the model. The model was educated with the help of supervised learning methods like SVMs and ANNs. Accuracy, sensitivity, specificity, and area under the curve were only a few of the criteria used to assess the model's efficacy. The results demonstrate that using demographic and clinical data, the model can effectively estimate individuals' cancer risk. Patient outcomes and healthcare costs may both benefit from this project's efforts to diagnose and treat cancer earlier. With AI and ML research at the forefront of academia, many new uses have been found for these technologies in recent years. It's not just some abstract concept out there; it's relevant to our daily lives, too. As this development continues, we see a closer integration of AI into medical practice. Its central premise also considerably reduced the current imbalance in medical distribution and the demand for available resources

    Study of HbA1c in Iron Deficiency Anemic Non Diabetic Subjects

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    To study the effect of iron deficiency anemia on glycated hemoglobin (HbA1c) in non- diabetic Indian subjects. The present observational study was performed on minimum 100 patients attending General Medicine outpatient department. All patients presenting to General Medicine outpatient department fulfilled the inclusion and exclusion criteria enrolled in the study. An informed written consent was obtained from the patients. The detailed history was taken and necessary clinical examination was carried out in all patients. In the current study, patients with iron deficiency anaemia had a mean HbA1c of 5.86. The mean serum iron level in patients with Hb1Ac levels ranging from 4-5.6 was 24.25. The corresponding mean serum iron for HbA1c range 5.7-6.4 was 22.25. The corresponding mean serum iron for HbA1c levels greater than 6.5 was 21.96. According to the findings, there is an inverse relationship between HbA1c and mean serum iron levels, and this relationship is statistically significant (p0.05), i.e. mean serum iron decreases as HbA1c level increases. The present study concluded that the levels of HbA1c were increased significantly among patients with iron deficiency anemia. So, Iron deficiency anemia has to be kept in mind before using the HbA1c to diagnose diabetes

    Comparative Evaluation of Effect of Extracting Solvents on Therapeutic Activities ofCurcuma AromaticaRhizomes: Therapeutic Potency of Different Extracts of Curcuma aromatica Rhizomes

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    There is the need for new drugs with better action and lesser side effects. A lot of research is being undertaken to find out new plant drugs, their extraction and pharmacological evaluation. One of such plant is Curcuma aromatica whichbelongs to the genus Curcuma and reported to have high ethno-botanical values in traditional medicine. The present study evaluates comparative pharmacological activity of four different extracts of Curcuma aromaticain healthy Wistar strain albino rats.Extraction of active constituents from powdered plant rhizomes was done by cold maceration technique using water, ethanol, hydroalcohol and toluene as solvents separately to get respective extracts. Acute oral toxicity study was performed to determine toxicity or side effects associated with the prepared plant extracts. The extracts were evaluated for anti-diabetic, anti-oxidant, anti-inflammatory and analgesic activity. Anti-diabetic activity was comparatively evaluated in alloxan induced diabetic rat models. Toluene extract was found to have relatively higher anti-diabetic activity. In vitro antioxidant potential of different extracts of was evaluated by DPPH radical scavenging activity. The results show anti-oxidant potency in toluene extract slightly better than other extracts. Aqueous extract of Curcuma aromatica rhizomes was found to have more potency in treatment of carrageenan induced paw oedema and also in its anti-nociceptive action against heat induced pain by Eddy’s hot plate method in rats.Though the anti-diabetic and anti-oxidant activities were slightly superior in toluene extract, the risk of residual amount of toluene remained in the final extract and its teratogenic property subdues its benefits of treatment.Findings of this research prove our hypothesis that oral administration of aqueous rhizome extract has potential anti-diabetic, anti-oxidant, anti-inflammatory and analgesic activities

    In-silico driven design and development of spirobenzimidazo-quinazolines as potential DNA gyrase inhibitors

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    DNA gyrase and Topoisomerase IV are promising antibacterial drug targets as they regulate bacterial DNA replication and topology. In a quest for novel DNA topoisomerase inhibitors, a multidisciplinary approach was adopted that involves computational prediction of binding sites and molecular modelling followed by green synthesis and biological evaluation of antibacterial activity of spirobenzimidazo quinazolines derivatives. Using basic quantum chemistry principles, we evaluated spirobenzimidazo quinazolines derivatives with their pharmacokinetic profiles. Based on the results of the aforesaid in-silico studies, we synthesized a series of titled compounds using green synthetic methodology that were validated as potential antimicrobial agents. Quantum chemoinformatics based predicted activity for the synthesized compounds 9b, 9c, and 9j was concomitant with biological evaluation of broadspectrum antibacterial activity. Biological evaluation revealed that inhibition of biofilm formation was due to their potential antibacterial activity. We believe that the novel spirobenzimidazo quinazolines have the potential to be alternatives to aminocoumarins and classical quinazolines upon detailed target specific biological studies

    Genetic and neuroanatomical support for functional brain network dynamics in epilepsy

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    Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention

    Maternal Footprints of Southeast Asians in North India

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    We have analyzed 7,137 samples from 125 different caste, tribal and religious groups of India and 99 samples from three populations of Nepal for the length variation in the COII/tRNALys region of mtDNA. Samples showing length variation were subjected to detailed phylogenetic analysis based on HVS-I and informative coding region sequence variation. The overall frequencies of the 9-bp deletion and insertion variants in South Asia were 1.9 and 0.6%, respectively. We have also defined a novel deep-rooting haplogroup M43 and identified the rare haplogroup H14 in Indian populations carrying the 9-bp deletion by complete mtDNA sequencing. Moreover, we redefined haplogroup M6 and dissected it into two well-defined subclades. The presence of haplogroups F1 and B5a in Uttar Pradesh suggests minor maternal contribution from Southeast Asia to Northern India. The occurrence of haplogroup F1 in the Nepalese sample implies that Nepal might have served as a bridge for the flow of eastern lineages to India. The presence of R6 in the Nepalese, on the other hand, suggests that the gene flow between India and Nepal has been reciprocal
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